Intuitionistic fuzzy EM-SWARA-TOPSIS approach based on new distance measure to assess the medical waste treatment techniques

Patel, Anjali; Jana, Subhankar; Mahanta, Juthika

doi:10.1016/j.asoc.2023.110521

Cited by 23 publications

(3 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The SWARA and WASPAS approaches have demonstrated their ability in many studies (Ghoushchi et al, 2022). For the SWARA method, Patel et al (2023) evaluated the sustainability criteria of a medical waste treatment method. Alkan (2024) assessed the orientation of RE systems toward sustainable development and utilization.…”

Section: Overview Of Studies Related To Swara and Waspas Methodsmentioning

confidence: 99%

A Decision-Making Model for Prioritizing Low-Carbon Policies in Climate Change Mitigation

Qiu,

Bouraima,

Badi

et al. 2024

CIS

View full text Add to dashboard Cite

Climate change (CC) represents a paramount environmental challenge, necessitating the deployment of sustainable, low-carbon strategies particularly in developing regions such as Africa. This study introduces a novel decision-making framework aimed at enhancing the prioritization of policies to combat the adverse effects of CC. The proposed two-stage model employs the integration of Step-Wise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) under spherical fuzzy (SF) conditions to address the strategic sequencing of sustainable policies. Initially, SF-SWARA is utilized to ascertain the relative significance of diverse criteria. Subsequently, the SF-WASPAS method ranks these policies, facilitating informed decision-making. The primary obstacles identified include limited institutional capacity, insufficient financial resources, and technological constraints, for which strategic alternatives are proposed. Moreover, rigorous sensitivity and comparative analyses affirm the model's applicability. By systematically delineating and prioritizing necessary policies, this study contributes significantly to the scholarly discourse on climate mitigation (CM) in an African context.

show abstract

Section: Overview Of Studies Related To Swara and Waspas Methodsmentioning

confidence: 99%

A Decision-Making Model for Prioritizing Low-Carbon Policies in Climate Change Mitigation

Qiu,

Bouraima,

Badi

et al. 2024

CIS

View full text Add to dashboard Cite

show abstract

“…The proposed method aims to guide future C-IFS MCDM methodologies. [13] It presents the IF-EM-SWARA-TOPSIS technique, which assesses HCW based on social, environmental, economic, and technical criteria in an intuitionistic fuzzy environment. The technique uses an entropy measure to evaluate objective weights of criteria, while the distance measure constructs a technique for order performance by similarity to ideal solution (TOPSIS).…”

Section: Public Year Referencesmentioning

confidence: 99%

Sustainable Medical Waste Management Using an Intuitionistic Fuzzy-Based Decision Support System

Kokkinos,

Lakioti,

Moustakas

et al. 2023

Sustainability

View full text Add to dashboard Cite

The growing urban population and increased use of healthcare services have brought significant attention to the safe and sustainable management of medical waste. Selecting the proper technology in medical waste management (MWM) represents one of the most critical challenges for decision-makers to ensure public health. In order to evaluate and choose the best MWM methodology, the current research provides a novel multi-criteria decision-making (MCDM) strategy for a variety of social stakeholders, to compute criteria weights, decision-making weights, and alternative ranking algorithms. The suggested structure addresses uncertain assessments of alternatives by extending weighting and ranking methods to acquire the decision-making weight and rank the MWM alternatives based on uncertain conditions. It also uses ‘intuitionistic fuzzy’ linguistic variables to indicate criteria weights. To assess all the factors pertaining to the sustainability of MWM actions, this study suggests the creation of a decision support system (DSS). Our DSS is built upon a novel strategy that utilizes a collection of MCDM models that are grounded on contemporary intuitionistic fuzzy logic methodologies. Alternative scenarios have been assessed for the instance of Greece, after specialists in the healthcare management field imposed 17 criteria and sub-criteria. The IF-MCDM methodologies used were the Intuitionistic Fuzzy DEMATEL, TOPSIS, and CORPAS. The alternative scenarios ranged from the prioritizing of safety laws and regulations to public acceptance and awareness, with the handling of hazardous risks and transportation playing a crucial part in the process. All ensemble methods produced the same ranking of the alternatives, demonstrating that safety and risk avoidance is the most significant scenario for sustainable urban development and public health.

show abstract

“…The TOPSIS Model has been well recognized for its geometric clarity, careful use of original data, little information loss, and wide applicability; nevertheless, when combined with intuitionistic fuzzy set theory, it is a groundbreaking development [18][19][20]. Together, they provide a potent new model that outperforms existing approaches.…”

Section: Introductionmentioning

confidence: 99%

Unveiling Water Quality Insights by Exploring Intuitionistic Fuzzy TOPSIS in Multi-criteria Decision Analysis

Mani,

Ranganathan

2024

MMEP

View full text Add to dashboard Cite

Intuitionistic fuzzy EM-SWARA-TOPSIS approach based on new distance measure to assess the medical waste treatment techniques

Cited by 23 publications

References 85 publications

A Decision-Making Model for Prioritizing Low-Carbon Policies in Climate Change Mitigation

A Decision-Making Model for Prioritizing Low-Carbon Policies in Climate Change Mitigation

Sustainable Medical Waste Management Using an Intuitionistic Fuzzy-Based Decision Support System

Unveiling Water Quality Insights by Exploring Intuitionistic Fuzzy TOPSIS in Multi-criteria Decision Analysis

Contact Info

Product

Resources

About